Temporal variation and controlling factors of canopy conductance in Artemisia ordosica community
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摘要: 冠层导度(gc)是影响植物蒸腾和光合作用的重要参数,对环境变化敏感。本研究利用涡度相关法于2015年5—10月对毛乌素沙地油蒿群落的潜热和显热通量进行连续观测,并同步观测空气温度(Ta)、相对湿度(RH)、光合有效辐射(PAR)、土壤含水量(VWC)、降雨(PP)等气象因子,结合Penman-Monteith的冠层导度逆转方程,了解gc时间动态与变异机制。结果表明:研究区油蒿群落gc日变化具有明显的季节差异,夏季(5—8月)gc达到峰值的时间比秋季(9—10月)早约2 h,约在10:00左右达到峰值,比水汽压亏缺(VPD)和PAR的峰值分别提前3~4 h和1~2 h,秋季gc在中午12:00达到峰值后直接下降。PAR、VPD均对gc有显著的调控作用,PAR和VPD对gc的调控阈值分别是1 200 μmol/(m2·s)和1.5 kPa,小于阈值呈正相关,大于阈值呈负相关。30 cm土壤含水量(VWC_30)是调控gc的重要因子,当VWC_30大于0.16 m3/m3时,gc与VWC_30呈正线性关系。在高的土壤含水量条件(VWC_30≥0.16 m3/m3)下,gc对PAR和VPD的敏感性高于低土壤含水量(VWC_30 < 0.16 m3/m3)条件。结果表明,土壤水分是调节荒漠生态系统冠层导度的关键因子,研究结果为荒漠生态系统水文过程模型的建立提供重要参考。Abstract: Canopy conductance (gc) is an important factor influencing plant transpiration and photosynthesis, and it is sensitive to environmental factors. Evapotranspiration and environmental factors of a shrub ecosystem, which was dominated by Artemisia ordosica in northwestern China, were continuously measured using eddy covariance technique in growing season (May-October) in 2015. Meteorological variables including air temperature (Ta), relative humidity (RH), photosynthetic active radiation (PAR), soil volumetric water content (VWC), and precipitation (PP) were also measured. gc was calculated using the inverted Penman-Monteith equation. Diurnal pattern in gc revealed a clear seasonal trend, with gc peaking 2 hours earlier in summer (from May to August) than autumn(from September to October)(10:00, 3-4 hours and 1-2 hours before VPD and PAR). During growing season, gc increased positively with vapor pressure deficit (VPD) and PAR, respectively, saturating at 1.5 kPa and 1 200 μmol/(m2·s), then decreasing with these variables when greater than their respective threshold.The gc values had positive relationship with soil volumetric water content at 30 cm depth (VWC_30) under high VWC_30 (≥0.16 m3/m3) during the whole growing season. gc was more responsive to PAR and VPD when VWC_30 was high. It was concluded that VWC played a critical role in regulating canopy conductance in desert ecosystems. Our results could potentially provide important baseline information towards hydrological model creation of arid and semi-arid ecosystems.
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Keywords:
- canopy conductance /
- soil water content /
- semiarid region /
- transpiration /
- photosynthesis
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图 6 30 cm土壤含水量对冠层导度和对gc与环境因子响应方式的影响
a.冠层导度(gc)对30 cm土壤含水量的响应;b.不同水分条件下gc对光合有效辐射(PAR)的响应;c.不同水分条件下gc对水汽压亏缺(VPD)的响应。
Figure 6. Effects of VWC at 30 cm depth (VWC_30) on gc and the way of gc responded to environment factors
a, response of canopy conductance (gc) to soil volumetric water content at 30 cm depth (VWC_30); b, response of gc to photosynthetic active radiation (PAR) under high and low VWC; c, response of gc to vapor pressure deficit (VPD) under high and low VWC.
表 1 不同30 cm土壤含水量冠层导度(gc)对光合有效辐射(PAR)和水汽压亏缺(VPD)的回归分析
Table 1 Regressions between canopy conductance (gc) and photosynthetic active radiation (PAR) and regressions between gc and vapor pressure deficit (VPD) under high and low soil volumetric water content at 30 cm depth (VWC_30)
PAR<1 200 μmol/(m2·s) PAR≥1 200 μmol/(m2·s) VPD<1.5 kPa VPD≥1.5 kPa VWC_30<0.16m3/m3 VWC_30≥0.16m3/m3 VWC_30<0.16m3/m3 VWC_30≥0.16m3/m3 VWC_30<0.16m3/m3 VWC_30≥0.16m3/m3 VWC_30<0.16m3/m3 VWC_30≥0.16m3/m2 a 0.001 3 0.001 7 -0.000 6 -0.001 8 0.56 0.81 0.67 0.95 b 0.43 0.46 2.43 4.66 0.57 0.73 1.95 2.31 R2 0.92 0.89 0.49 0.94 0.82 0.90 0.75 0.68 注:gc与PAR的拟合方程为:gc=a·PAR+b,a和b为线性回归分析得出的系数,R2为相关系数。当VPD<1.5 kPa,gc与VPD的拟合方程为:gc=a·VPD+b,a和b为线性回归分析得出的系数。当VPD≥1.5 kPa,gc与VPD的拟合方程为:gc=-alnVPD+b,a和b为非线性回归分析得出的系数。Notes:the a and b in fitting equation of gc and PAR are coefficients obtained by linear regression analysis as the following equation form:gc=a·PAR+b, the letter R2 stands for the correlation coefficient. When VPD<1.5 kPa, the a and b in fitting equation of gc and VPD are coefficients obtained by linear regression analysis as the following equation form:gc=a·VPD+b, the letter R2 stands for the correlation coefficient. When VPD≥1.5 kPa, the a and b in fitting equation of gc and VPD are coefficients obtained by non-linear regression analysis as the following equation form:gc=-alnVPD+b, the letter R2 stands for the correlation coefficient. -
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